# cor2cov: Converting a correlation matrix into a covariance matrix In propagate: Propagation of Uncertainty

## Description

Converts a correlation matrix into a covariance matrix using variance information. It is therefore the opposite of cov2cor.

## Usage

 1 cor2cov(C, var) 

## Arguments

 C a symmetric numeric correlation matrix \mathbf{C}. var a vector of variances σ_n^2.

## Details

Calculates the covariance matrix \mathbf{Σ} using a correlation matrix \mathbf{C} and outer products of the standard deviations σ_n:

\mathbf{Σ} = \mathbf{C} \cdot σ_n \otimes σ_n

## Value

The corresponding covariance matrix.

## Author(s)

Andrej-Nikolai Spiess

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 ## Example in Annex H.2 from the GUM 2008 manual ## (see 'References'), simultaneous resistance ## and reactance measurement. data(H.2) attach(H.2) ## Original covariance matrix. COV <- cov(H.2) ## extract variances VAR <- diag(COV) ## cor2cov covariance matrix. COV2 <- cor2cov(cor(H.2), VAR) ## Equal to original covariance matrix. all.equal(COV2, COV) 

### Example output

Loading required package: MASS
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package:bit (c) 2008-2012 Jens Oehlschlaegel (GPL-2)
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bit access: length<- [ [<- [[ [[<-
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Attaching package: 'bit'

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Attaching package ff
- getOption("fftempdir")=="/work/tmp/tmp/Rtmpbd0XpW"

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- getOption("ffcaching")=="mmnoflush"  -- consider "ffeachflush" if your system stalls on large writes

- getOption("ffbatchbytes")==16777216 -- consider a different value for tuning your system

- getOption("ffmaxbytes")==536870912 -- consider a different value for tuning your system

Attaching package: 'ff'

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